ISAT: An intelligent Web service selection approach for improving reliability via two-phase decisions

Due to stochasticity and uncertainty of malicious Web services over the Internet, it becomes difficult to select reliable services while meeting non-functional requirements in service-oriented systems. To avoid the unreliable real-world process of obtaining services, this paper proposes a novel service selection approach via two-phase decisions for enhancing the reliability of service-oriented systems. In the first-phase decision, we define the problem of finding reliable service candidates as a multiple criteria decision making (MCDM) problem. Then, we construct a decision model to address the problem. In the second-phase decision, we define the problem of selecting services based on non-functional requirements as an optimization problem. Finally, we propose a convex hull based approach for solving the optimization problem. Large-scale and real-world experiments are conducted to show the advantages of the proposed approach. The evaluation results confirm that our approach achieves higher success rate and less computation time to guarantee the reliability when compared to the other state-of-the-art approaches.